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• W1907157432 abstract "The class of generalized autoregressive conditional heteroscedastic (GARCH) models has proved particularly valuable in modelling time series with time varying volatility. These include financial data, which can be particularly heavy tailed.This paper investigates the time-series behavior of stock returns for Zimbabwe stock market. In most cases, higher average returns appear to be associated with a higher level of volatility. Testing the relationship between stock returns and unexpected volatility, the evidence shows that the Industrial Stock Market has significant results whilst the Mining Stock Market shows a different behaviour. A trend analysis of the nominal prices of stocks is done as well as trend analysis of the generated stock returns for both markets. Trend analysis enables the performance of the stock market to be noticed over time. Trend Analysis has favoured the Industrial Stock Market over the Mining Stock Market. The study concludes that there is need to develop the mining sector to attract investors as its growth is showing a downward trend." @default.
• W1907157432 created "2016-06-24" @default.
• W1907157432 creator A5058440722 @default.
• W1907157432 creator A5064812119 @default.
• W1907157432 date "2014-02-23" @default.
• W1907157432 modified "2023-09-24" @default.
• W1907157432 title "Empirical Analysis of Stock Returns and Volatilityof the Zimbabwean Stock Markets" @default.
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• W1907157432 doi "https://doi.org/10.6084/m9.figshare.1284636" @default.
• W1907157432 hasPublicationYear "2014" @default.
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